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Llama-3.2-1B-Instruct-safetyquant-c2
Jeesup/Llama-3.2-1B-Instruct-safetyquant-c2
Llama-3.2-1B-Instruct-safetyquant-c2 is a machine learning model from Jeesup. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Quantized variant used in the Safety-Aware Configuration-Conditioned LoRA study.
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From the Hugging Face model README
Llama-3.2-1B-Instruct — configuration c2 (W4A16)
Quantized variant used in the Safety-Aware Configuration-Conditioned LoRA study.
| field | value |
|---|---|
| scheme | W4A16 |
| method | gptq |
| simulated | no — native kernel |
| weight bits | 4 |
| activation bits | 16 |
| group / block size | 128 |
| symmetric | True |
| calibration | 512 × 2048 tok, C4 |
| calibration sha256 | b5736155d5b24bf5eb15faae0eb4a742aea4a9d0532db9684085a49750606e19 |
The calibration set is byte-identical across every configuration so that calibration data cannot be confounded with quantization method. c2 vs c3 isolates method (GPTQ vs AWQ) at equal bit-width, and is the study's headline control: 0.0276 vs 0.0661 pooled ASR with non-overlapping 95% CIs.
Metrics, per-prompt judge verdicts and the full report: Jeesup/safety-quant-phase0.
- Type
- llama
- Created
- Aug 9, 2026
- Updated
- Aug 10, 2026